Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells

Jayashree Sahana1, José Luis Cortés-Sánchez2, Viviann Sandt2

  • 1Department of Biomedicine, Aarhus University, 8000 Aarhus, Denmark.

Insights

Simulated microgravity using a random positioning machine (RPM) alters gene expression in breast cancer cells. This 3D multicellular spheroid (MCS) model mimics metastatic environments, offering a platform for future breast cancer drug efficacy studies.

Area of Science:

  • Cell Biology
  • Space Biology
  • Oncology

Background:

  • Microgravity significantly impacts cellular gene expression patterns.
  • Breast cancer cell lines, such as MCF-7 and MDA-MB-231, exhibit varying invasiveness.
  • Understanding cellular behavior in altered gravity is crucial for space exploration and terrestrial medicine.

Purpose of the Study:

  • To investigate the effects of simulated microgravity (s-µg) on breast cancer cell lines (MCF-7 and MDA-MB-231).
  • To analyze changes in cytoskeletal, extracellular matrix (ECM), focal adhesion (FA), and signaling pathway gene expression.
  • To evaluate the utility of a microgravity-engineered 3D multicellular spheroid (MCS) model for studying breast cancer.

Main Methods:

  • Cells were cultured for 14 days under s-µg using a random positioning machine (RPM).
  • Quantitative real-time PCR (qPCR) was used to determine mRNA expression of 24 key genes.
  • STRING interaction analysis, histochemical staining, and weighted gene co-expression network analysis (WGCNA) were employed.

Main Results:

  • Simulated microgravity induced significant changes in gene expression related to cytoskeleton, ECM, and cellular signaling pathways.
  • The 3D MCS model showed a positive association with the metastatic microtumor environment.
  • Morphological and molecular profiles of MCSs under s-µg mirrored aspects of in vivo tumor progression.

Conclusions:

  • The microgravity-engineered 3D MCS model effectively simulates aspects of the metastatic breast cancer microenvironment.
  • This model provides a valuable platform for studying breast cancer cell behavior.
  • The model holds potential for assessing the therapeutic efficacy of anti-cancer drugs in a more relevant context.

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